Tumor classification is an essential part of the disease management process as it is used by the clinician to help guide the treatment regimen. It is known that great diversity exists within most solid tumors that have a common tissue of origin, like breast, and that there is even significant diversity in clinical behavior within what are described as morphologically similar tumors. Traditional approaches to breast tumor classification have utilized a mixture of empirical criteria including a morphological assessment, measures of the extent of disease dissemination, and a handful of statistically validated prognostic and predictive markers. There is a consensus, however, that these current methods fall short of the challenges posed by breast tumor diversity. The development of modern genomic analysis tools, in particular cDNA microarrays, allows us the opportunity to objectively and without foreknowledge, determine the expression level of thousands of genes in a single sample/tumor in a single day. We hypothesized that the phenotypic diversity of breast tumors would be accompanied by a corresponding diversity in gene expression patterns that we could capture using cDNA microarrays, and that this gene expression diversity could then be used to classify tumors into groups of clinical importance. We will approach the objective of defining new prognostic and predictive markers for breast cancer outcomes and response to therapy through the following specific aims: Specific Aim 1: To identify as many as possible of the biologically and clinically relevant breast tumor subtypes by assaying 150-250 more grossly dissected human breast tumors versus a "common reference sample" on cDNA microarrays containing at least 20,000 genes. Several patient cohorts with both pre- and post-chemotherapy samples will be assayed. These data will be combined with our already existing data to build an extensive database of breast tumor gene expression "profiles" that will used to further refine our breast tumor classifications and to search for correlations between gene expression patterns and responses to chemotherapy. Specific Aim 2: To further develop a protocol for the utilization of small amounts of input RNA for cDNA microarray analysis. Techniques that lower the amount of input RNA required for a microarray experiment will be pursued so that a larger and more representative sampling of breast tumors can be performed, and so that the core biopsy specimens described in SPORE Project 17 can be analyzed on microarrays. Specific Aim 3: Determine the global gene expression profiles of the prospective cohort of 120 breast cancer patients from UNC hospitals who will receive a neoadjuvant anthracycline-based and taxane-based chemotherapy regimen (Dr. Carey?s Project 17), and identify sets of genes that are associated with, and may be predictive of, response or resistance to specific chemotherapeutics.